Brief Robust one-step receding horizon control of discrete-time Markovian jump uncertain systems

Authors:
Byung-Gun Park;Wook Hyun Kwon
Affiliations:
Media Lab, Samsung IT Center, Samsung Electronics, 14th Fl., 416, Maetan 3 Dong, Paldal-Gu, Suwon-Shi, Kyunggi-Do 442-742, South Korea;School of Electrical Engineering and ERC-ACI, Seoul National University, Seoul 151-742, South Korea
Venue:
Automatica (Journal of IFAC)
Year:
2002

Citing 5
Cited 1

A Convex Approach to the Mixed ${\cal H}_{2}/{\cal H}_\infty$Control Problem for Discrete-Time Uncertain Systems

SIAM Journal on Control and Optimization
Semidefinite programming

SIAM Review
Robust constrained model predictive control using linear matrix inequalities

Automatica (Journal of IFAC)
Quasi-Min-Max MPC algorithms for LPV systems

Automatica (Journal of IFAC)
Brief Constrained quadratic state feedback control of discrete-time Markovian jump linear systems

Automatica (Journal of IFAC)

Robust model predictive control for fuzzy systems subject to actuator saturation

FSKD'09 Proceedings of the 6th international conference on Fuzzy systems and knowledge discovery - Volume 6

Quantified Score

Hi-index	22.14

Visualization

Abstract

This paper proposes a receding horizon control scheme for a set of uncertain discrete-time linear systems with randomly jumping parameters described by a finite-state Markov process whose jumping transition probabilities are assumed to belong to some convex sets. The control scheme for the underlying systems is based on the minimization of the worst-case one-step finite horizon cost with a finite terminal weighting matrix at each time instant. This robust receding horizon control scheme has a more general structure than the existing robust receding horizon control for the underlying systems under the same design parameters. The proposed controller is obtained using semidefinite programming.